Overview & Capability
Standardized API specifications and reference runtimes by Meta for building end-to-end RAG, tool calling, agentic execution loops, and synthetic data pipelines with Llama models.
Key Highlights
- Standardized agent memory, inference, and tool execution APIs
- Pluggable backends across Ollama, Together AI, Fireworks, and AWS
- Built-in evaluation, safety guardrails, and telemetry
Robbie's Independent Take
Verified: 2026-10-11
Excellent candidate for local execution with zero cloud lock-in. For 7B-8B parameter models, budget at least 8 GB of unified memory or VRAM (Q4_K_M quantization). For 32B-70B models, aim for 24 GB+ to maintain interactive throughput without CPU offload penalties.
Alternatives & Replaces
- Fragmented bespoke agent plumbing